A coupled Bayesian and fault tree methodology to assess future groundwater conditions in light of climate change
J. J. Huang1, M. Du2, E. A. McBean3, H. Wang1, and J. Wang11State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin, China Institute of Water Resources and Hydropower Research, Beijing, 100038, China 2Polytech Nice-Sophia, 930 Route des Colles, 06903 Sophia Antipolis, France 3School of Engineering, University of Guelph, Guelph, ON, N1G 2W1, Canada
Received: 18 Jun 2014 – Accepted for review: 07 Jul 2014 – Discussion started: 06 Aug 2014
Abstract. Maintaining acceptable groundwater levels, particularly in arid areas, while protecting ecosystems, are key measures against desertification. Due to complicated hydrological processes and their inherent uncertainties, investigations of groundwater recharge conditions are challenging, particularly in arid areas under climate changing conditions. To assist planning to protect against desertification, a fault tree methodology, in conjunction with fuzzy logic and Bayesian data mining, are applied to Minqin Oasis, a highly vulnerable regime in northern China. A set of risk factors is employed within the fault tree framework, with fuzzy logic translating qualitative risk data into probabilities. Bayesian data mining is used to quantify the contribution of each risk factor to the final aggregated risk. The implications of both historical and future climate trends are employed for temperature, precipitation and potential evapotranspiration (PET) to assess water table changes under various future scenarios. The findings indicate that water table levels will continue to drop at the rate of 0.6 m yr−1 in the future when climatic effects alone are considered, if agricultural and industrial production capacity remain at 2004 levels.
Huang, J. J., Du, M., McBean, E. A., Wang, H., and Wang, J.: A coupled Bayesian and fault tree methodology to assess future groundwater conditions in light of climate change, Hydrol. Earth Syst. Sci. Discuss., 11, 9361-9397, doi:10.5194/hessd-11-9361-2014, 2014.